AI Software Engineer - C++ - GPGPU - CUDA - openCL The ideal candidate will have experience and expertise in both GPU compute programming and systems development using modern C++. The prospective candidate will work on and grow in both directions. This position will require the candidate to work closely with researchers and … s or higher degree in Computer Science/Engineering or related disciplines Professional software development experience with modern C++ Experience with GPU compute in CUDA/OpenCL Knowledge of linear algebra equivalent to at least first-year university level Strong computer science and engineering fundamentals (e.g., OS, Compiler) Familiarity more »
Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively in cross-functional teams and present complex ideas more »
Linux kernel Be familiar with C or C++, and master at least one of other languages such as Python/Golang/Rust/Cuda Familiar with common data structure and algorithm, multithreading programming and multithreading program performance optimization Any of the following would be considered a plus: Able more »
/Video processing for a brand-new cutting edge project. They need someone with very strong C++ skills, as well as strong exposure to CUDA or OpenCL. If you are interested in working on the cutting edge of HPC/GPU optimisation, don't hesitate to apply (even if … fit the bill!) About you: 5+ years in a Software Engineering role (with a C++ and GPU element) Interest in performance optimisation Exposure to CUDA, OpenCL or GPGPU Passion for clean, reliable code Full details are available. Please don't hesitate to get in touch with max@platform-recruitment.com more »
art optimisation capabilities to leading Trading and AI firms alike. They need someone with very strong C++ skills, as well as strong exposure to Cuda . If you are interested in working on the cutting edge of HPC/GPU optimisation, don't hesitate to apply (even if you more »
in software engineering, with a focus on developing and deploying production-grade applications, Working experience with ROS2, Development experience with parallel computing such as CUDA, OpenMP, SSE, etc, Experience with Atlassian tools; Jira, GitLab, Confluence, Experience taking ML models to production, Hands-on experience with popular machine learning frameworks more »
In-depth understanding of security best practices and experience in implementing secure software architectures Openstack experience is highly desirable Familiarity with GPU programming (e.g., CUDA, OpenCL) and HPC is desirable What We Offer: Competitive salary Opportunity to work with a diverse team of talented professionals who are passionate about more »
Computer Science, Engineering, or a related technical discipline or equivalent experience Strong software engineering experience in Python and other relevant languages (e.g. C++ and CUDA) Direct experience working in at least one of computer vision, robotics, simulation, graphics, or large language models. MS, or above in Machine Learning, Computer more »
research solutions into the product The role will be exposed to a broad tech stack (e.g. ReactJS, Python, REST & GraphQL, OpenCV, PyTorch, GCP, AWS & CUDA, Kubernetes) and the cutting edge of computer vision and deep learning. Qualifications The right candidate will have a proven track record of relevant publications more »
for C++ developers with experience designing low-latency real-time video or image processing software. Strong knowledge of Nvidia Holoscan, Deepstream, or Gstreamer and CUDA or OpenCL is also highly preferred. #J-18808-Ljbffr more »
open environment Ability to be a mentor, coach, and sponsor to peers and colleagues Nice to haves: PyTorch, NumPy, Pandas, GCP, Hybrid Cloud, Linux, CUDA, Docker, Kubernetes, SLURM, BigQuery, large scale distributed systems How You ll be Supported A member of the ML Infra team will be your trail more »
on proficiency in C/C++. 3.Working experience in GPU or GPGPU UMD driver development. 4.Proficiency and working experience with GPGPU APIs such as CUDA/HIP/OpenCL. Preferred Qualifications: 5.Familiarity with CUDA or ROCm development and debugging. 6.Good understanding of GPU hardware/software architecture, including more »
about efficient large-scale training, low-latency inference in real-time systems and high-throughput inference in research. Part of this is improving straightforward CUDA, but the interesting part needs a whole-systems approach, including storage systems, networking and host- and GPU-level considerations. Zooming in, we also want … end Low-level GPU knowledge of PTX, SASS, warps, cooperative groups, Tensor Cores and the memory hierarchy Debugging and optimisation experience using tools like CUDA GDB, NSight Systems, NSight Computesight-systems and nsight-compute Library knowledge of Triton, CUTLASS, CUB, Thrust, cuDNN and cuBLAS Intuition about the latency and … throughput characteristics of CUDA graph launch, tensor core arithmetic, warp-level synchronization and asynchronous memory loads Background in Infiniband, RoCE, GPUDirect, PXN, rail optimisation and NVLink, and how to use these networking technologies to link up GPU clusters An understanding of the collective algorithms supporting distributed GPU training in more »
about efficient large-scale training, low-latency inference in real-time systems and high-throughput inference in research. Part of this is improving straightforward CUDA, but the interesting part needs a whole-systems approach, including storage systems, networking and host- and GPU-level considerations. Zooming in, we also want … end Low-level GPU knowledge of PTX, SASS, warps, cooperative groups, Tensor Cores and the memory hierarchy Debugging and optimisation experience using tools like CUDA GDB, NSight Systems, NSight Computesight-systems and nsight-compute Library knowledge of Triton, CUTLASS, CUB, Thrust, cuDNN and cuBLAS Intuition about the latency and … throughput characteristics of CUDA graph launch, tensor core arithmetic, warp-level synchronization and asynchronous memory loads Background in Infiniband, RoCE, GPUDirect, PXN, rail optimisation and NVLink, and how to use these networking technologies to link up GPU clusters An understanding of the collective algorithms supporting distributed GPU training in more »
